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Falcon Mamba 7B

TII's pure-Mamba 7B — the first attention-free open model to beat transformer rivals at this scale.

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About

Falcon Mamba 7B is the Technology Innovation Institute's base large language model built on the pure Mamba state-space architecture, trained on 5.8 trillion tokens of curated data. Its technical report showed it surpassing transformer-based open-weight models like Mistral 7B, Llama 3.1 8B, and Falcon2 11B, while matching Gemma 7B — demonstrating that even a pure (non-hybrid) Mamba design can equal or exceed transformer and hybrid designs at this scale.

Because the architecture processes tokens sequentially in linear time, Falcon Mamba is significantly faster at inference and needs far less memory for long sequence generation than its transformer peers. Released in August 2024 under the permissive TII Falcon-Mamba License 2.0 (Apache-2.0-based), it remains the reference implementation for state-space language modeling in the open ecosystem.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

August 13, 2024

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

language-modelinglong-contextefficient-inference

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 69; Trending score 70/100 from researcher assessment.

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Sources